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Estimating irrigation water use for maize in the Southeastern USA: A modeling approach

Author

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  • Salazar, M.R.
  • Hook, J.E.
  • Garcia y Garcia, A.
  • Paz, J.O.
  • Chaves, B.
  • Hoogenboom, G.

Abstract

Increased crop production and expansion of irrigated acreage in the southeastern USA have increased agricultural water use during the past two decades. To optimize irrigation water use, it is important to know when to irrigate and how much water should be applied. The objectives of this study were (1) to evaluate the Cropping System Model (CSM)-CERES-Maize model with measured data of the amount of water required for supplemental irrigation and (2) to apply the CSM-CERES-Maize model for estimating irrigation water use for maize in the southeastern USA. The CSM-CERES-Maize model was evaluated for 2000–2004 for five counties that represent the dominant maize production regions in South Georgia. For each county, historical daily weather data, three representative soil profiles, and specific crop management recommendations were used as input for the model. The simulated results were then compared with observed data obtained during the same period. The amount of water required for irrigation for each growing season was simulated for 58 years using historical weather data from 1950 to 2007 for 88 selected counties that corresponded to the most important agricultural production region in Georgia. Both monthly and annual water demand for maize was determined for each county. The total seasonal amount of water required for irrigation across counties and years ranged from 136 to 281mm, with an average of 227mm. The irrigation requirements among months varied from 10 to 79mm, with the highest amount required for May. The results from the evaluation showed that the model was able to simulate the amount of water required for maize irrigation in good agreement with the observed data. This demonstrated the potential application of the CSM-CERES-Maize model as a tool for estimating water demand for irrigation. The estimated water requirements for supplemental irrigation can be used by both policy makers and local farmers for planning the amount of water required for supplemental irrigation as well as for improvements in irrigation management for water conservation.

Suggested Citation

  • Salazar, M.R. & Hook, J.E. & Garcia y Garcia, A. & Paz, J.O. & Chaves, B. & Hoogenboom, G., 2012. "Estimating irrigation water use for maize in the Southeastern USA: A modeling approach," Agricultural Water Management, Elsevier, vol. 107(C), pages 104-111.
    • Handle: RePEc:eee:agiwat:v:107:y:2012:i:c:p:104-111
    DOI: 10.1016/j.agwat.2012.01.015
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    1. Guerra, L.C. & Garcia y Garcia, A. & Hook, J.E. & Harrison, K.A. & Thomas, D.L. & Stooksbury, D.E. & Hoogenboom, G., 2007. "Irrigation water use estimates based on crop simulation models and kriging," Agricultural Water Management, Elsevier, vol. 89(3), pages 199-207, May.
    2. Mullen, Jeffrey D. & Yu, Yingzhuo & Hoogenboom, Gerrit, 2009. "Estimating the demand for irrigation water in a humid climate: A case study from the southeastern United States," Agricultural Water Management, Elsevier, vol. 96(10), pages 1421-1428, October.
    3. Persson, Tomas & Garcia y Garcia, Axel & Paz, Joel & Jones, Jim & Hoogenboom, Gerrit, 2009. "Maize ethanol feedstock production and net energy value as affected by climate variability and crop management practices," Agricultural Systems, Elsevier, vol. 100(1-3), pages 11-21, April.
    4. Nijbroek, Ravic & Hoogenboom, Gerrit & Jones, James W., 2003. "Optimizing irrigation management for a spatially variable soybean field," Agricultural Systems, Elsevier, vol. 76(1), pages 359-377, April.
    5. Garrison, M. V. & Batchelor, W. D. & Kanwar, R. S. & Ritchie, J. T., 1999. "Evaluation of the CERES-Maize water and nitrogen balances under tile-drained conditions," Agricultural Systems, Elsevier, vol. 62(3), pages 189-200, December.
    6. Nuti, R.C. & Lamb, M.C. & Sorensen, R.B. & Truman, C.C., 2009. "Agronomic and economic response to furrow diking tillage in irrigated and non-irrigated cotton (Gossypium hirsutum L.)," Agricultural Water Management, Elsevier, vol. 96(7), pages 1078-1084, July.
    7. Ruiz-Nogueira, B. & Boote, K. J. & Sau, F., 2001. "Calibration and use of CROPGRO-soybean model for improving soybean management under rainfed conditions," Agricultural Systems, Elsevier, vol. 68(2), pages 151-173, May.
    8. K.J. Boote & J.W. Jones & G. Hoogenboom & J.W. White, 2010. "The Role of Crop Systems Simulation in Agriculture and Environment," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global, vol. 1(1), pages 41-54, January.
    9. Garcia y Garcia, Axel & Guerra, Larry C. & Hoogenboom, Gerrit, 2008. "Impact of generated solar radiation on simulated crop growth and yield," Ecological Modelling, Elsevier, vol. 210(3), pages 312-326.
    10. Hook, James E., 1994. "Using crop models to plan water withdrawals for irrigation in drought years," Agricultural Systems, Elsevier, vol. 45(3), pages 271-289.
    11. Panda, R. K. & Behera, S. K. & Kashyap, P. S., 2004. "Effective management of irrigation water for maize under stressed conditions," Agricultural Water Management, Elsevier, vol. 66(3), pages 181-203, May.
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    2. Phetheet, Jirapat & Hill, Mary C. & Barron, Robert W. & Gray, Benjamin J. & Wu, Hongyu & Amanor-Boadu, Vincent & Heger, Wade & Kisekka, Isaya & Golden, Bill & Rossi, Matthew W., 2021. "Relating agriculture, energy, and water decisions to farm incomes and climate projections using two freeware programs, FEWCalc and DSSAT," Agricultural Systems, Elsevier, vol. 193(C).
    3. Fan, Yubing & McCann, Laura M., 2017. "Farmers’ Adoption of Pressure Irrigation Systems and Scientific Scheduling Practices: An Application of Multilevel Models," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258458, Agricultural and Applied Economics Association.
    4. Pilar Benito-Verdugo & José Martínez-Fernández & Ángel González-Zamora & Laura Almendra-Martín & Jaime Gaona & Carlos Miguel Herrero-Jiménez, 2023. "Impact of Agricultural Drought on Barley and Wheat Yield: A Comparative Case Study of Spain and Germany," Agriculture, MDPI, vol. 13(11), pages 1-20, November.
    5. Boyer, Christopher N. & Larson, James A. & Roberts, Roland K. & McClure, Angela T. & Tyler, Donald D. & Smith, S. Aaron, 2014. "Probability of Irrigated Corn Being Profitable in a Humid Region," 2014 Annual Meeting, February 1-4, 2014, Dallas, Texas 162470, Southern Agricultural Economics Association.
    6. Fan, Yubing & Massey, Raymond E. & Park, Seong C., 2017. "Multicrop Production Decisions and Economic Irrigation Water Use Efficiency: Effects of Water Costs, Pressure Irrigation Adoption and Climate Determinants," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258561, Agricultural and Applied Economics Association.

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